Hereβs your 9-Month Structured Program version of the course content you provided, clearly broken down month-wise to reflect a comprehensive and progressive learning path:
From zero to job-ready, this 9-month intensive program is designed with a project-driven and hands-on approach to ensure real-world exposure. Youβll master Cloud Platforms (AWS & Azure), DevSecOps tools, Machine Learning with Python, and crack interviews with DSA and problem-solving mastery.
Core Services: EC2, S3, IAM, RDS, EBS
Networking: VPC, Load Balancer, Route 53
Hands-on: Launch and manage services using AWS Console and CLI
Serverless: Lambda, API Gateway, DynamoDB
Monitoring & DevOps Tools: CloudWatch, CodePipeline, CodeDeploy
Project: Host a scalable web app
Certification Prep: AWS Cloud Practitioner / Architect Associate
DevOps Lifecycle Overview
Version Control: Git, GitHub
CI/CD Setup: Jenkins, Maven
Project Management: Jira
Code Quality & Security: SonarQube, SAST/DAST
Containerization & IaC: Docker, Kubernetes, Terraform, Ansible
Real-Time Project: Secure CI/CD Pipeline Deployment
Python Essentials: Numpy, Pandas, Matplotlib
ML Algorithms: Regression, Classification, Clustering
Project: Sentiment Analysis, Stock Prediction
Model Evaluation, Hyperparameter Tuning
Project: End-to-End ML Project
Model Deployment: Flask + AWS/Azure (Optional)
Core Python + OOPs Concepts
Data Structures: Arrays, Strings, Lists
Logic Building & Problem Solving
Advanced Structures: Trees, Graphs, Recursion
Sorting, Searching, Time Complexity
Practice: Leetcode-style challenges
Capstone Projects Across All Tech Stacks
Mock Interviews & Problem Solving
Resume Building & Placement Support
Crack Tech Interviews with Confidence
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4-in-1 Mastery: Cloud + DevSecOps + ML + DSA
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Project-Based Learning with Real-Time Deployment
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Industry-Grade Tools: Git, Jenkins, Docker, Terraform
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Global Certifications Support
Let me know if you want this in brochure or PDF format as well.
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βοΈ Cloud Computing with ML Ops β Beginner to Advanced (9 Months) Master the future of tech by combining Cloud Computing, DevOps, and Machine Learning Operations (ML Ops) in one powerful program. This 9-month course takes you from foundational cloud skills to advanced ML deployment, including AWS/GCP, Docker, Kubernetes, Python, MLflow, and more. Learn by building real-world projects and get certified with industry-recognized credentials. Ideal for those aiming to become Cloud ML Engineers, ML Ops Specialists, or DevOps Engineers with AI expertise.
Learn the advance data engineering of Azure setup, user management, and directory services.
Learn AWS (20+ services), Azure, Git, GitHub, Docker, Kubernetes, Jenkins, Terraform, JIRA, Maven, Ant, and SonarQube. Perfect for IT professionals aiming to build CI/CD pipelines, automate infrastructure, and deploy secure, scalable applications. 100% pre-recorded sessions, hands-on labs, and certification included.